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      PlotsOfData—A web app for visualizing data together with their summaries

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      PLoS Biology
      Public Library of Science

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Reporting of the actual data in graphs and plots increases transparency and enables independent evaluation. On the other hand, data summaries are often used in graphs because they aid interpretation. To democratize state-of-the-art data visualization of raw data with a selection of statistical summaries, a freely available, open-source web app was written using R/shiny that uses the ggplot2 package for generating plots. Users can to choose how to display the data and which of the data summaries to add. In addition, the 95% confidence intervals (95CIs) can be added for visual inferences. By adjusting the visibility of the layers, the visualization of the raw data and their summaries can be tuned for optimal presentation and interpretation. The app is dubbed PlotsOfData and is available at https://huygens.science.uva.nl/PlotsOfData/.

          Abstract

          This Community Page article describes PlotsOfData, an intuitive web-based tool for state-of-the-art visualization of data and statistics, without the need for coding skills.

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          Most cited references12

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          Statistical methods in psychology journals: Guidelines and explanations.

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            BoxPlotR: a web tool for generation of box plots.

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              Inference by eye: confidence intervals and how to read pictures of data.

              Wider use in psychology of confidence intervals (CIs), especially as error bars in figures, is a desirable development. However, psychologists seldom use CIs and may not understand them well. The authors discuss the interpretation of figures with error bars and analyze the relationship between CIs and statistical significance testing. They propose 7 rules of eye to guide the inferential use of figures with error bars. These include general principles: Seek bars that relate directly to effects of interest, be sensitive to experimental design, and interpret the intervals. They also include guidelines for inferential interpretation of the overlap of CIs on independent group means. Wider use of interval estimation in psychology has the potential to improve research communication substantially. ((c) 2005 APA, all rights reserved).
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                Author and article information

                Journal
                PLoS Biol
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, CA USA )
                1544-9173
                1545-7885
                27 March 2019
                March 2019
                27 March 2019
                : 17
                : 3
                : e3000202
                Affiliations
                [001]Swammerdam Institute for Life Sciences, Section of Molecular Cytology, van Leeuwenhoek Centre for Advanced Microscopy, University of Amsterdam, Amsterdam, the Netherlands
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-0630-3825
                Article
                PBIOLOGY-D-18-01445
                10.1371/journal.pbio.3000202
                6453475
                30917112
                2aa56fa9-7f95-4e39-9a12-cf5eb1c14717
                © 2019 Postma, Goedhart

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 4, Tables: 0, Pages: 8
                Funding
                The authors received no specific funding for this work.
                Categories
                Community Page
                Computer and Information Sciences
                Data Visualization
                Computer and Information Sciences
                Data Visualization
                Infographics
                Graphs
                Physical Sciences
                Mathematics
                Statistics
                Statistical Data
                Physical Sciences
                Mathematics
                Statistics
                Confidence Intervals
                Computer and Information Sciences
                Software Engineering
                Software Tools
                Engineering and Technology
                Software Engineering
                Software Tools
                Computer and Information Sciences
                Computer Software
                Open Source Software
                Science Policy
                Open Science
                Open Source Software
                Computer and Information Sciences
                Software Engineering
                Source Code
                Engineering and Technology
                Software Engineering
                Source Code
                Computer and Information Sciences
                Computer Networks
                Internet
                Custom metadata
                vor-update-to-uncorrected-proof
                2019-04-08

                Life sciences
                Life sciences

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